The aim in computed tomography imaging, as well as obtaining a good image quality, is also that the respective examination volume absorbs an x-ray dose that is as small as possible, since a high x-ray dose can lead to potential damage to parts of the examination volume. This aim is also referred to as ALARA (an acronym for “as low as reasonably achievable”).
In such cases, with an increasing x-ray dose, the noise in the resulting image dataset generally decreases, whereby the image quality increases. Computed tomography imaging can thus be referred to as optimum when the image quality is selected as just good enough, and thus when the x-ray dose is just high enough to still make a unique diagnosis of the resulting image possible. It is therefore usual to include dose parameters, for planning and/or for evaluating computed tomography imaging.
It is known that a dose parameter can be calculated in relation to an axial slice plane of the examination volume based on an axial slice image and further recording parameters, for example by way of a Monte-Carlo simulation. Here however the x-ray dose can only be calculated after the computed tomography imaging, thus the x-ray dose here is only a result of the computed tomography imaging. Furthermore, with this method, very many slice images must be transmitted and analyzed, if the x-ray dose is to be determined in a larger region of the examination volume, moreover a large amount of computing time must be expended for this calculation.
It is further known that a dose parameter can be calculated based solely on the recording parameters of a computed tomography imaging. This calculation is done specifically only for a particular manufacturer of computed tomography devices or even more specifically for only one type of computed tomography device. This only enables the dose parameter calculated in each case to be compared with restrictions between computed tomography devices of different manufacturers or between different types. Furthermore the dose parameter calculated in each case is not tailored individually to the patient.
The disadvantages of the large volume of data and of the poor comparability become evident above all when pan-device or pan-hospital evaluations of the dose parameter are to be carried out by way of an environment for distributed computing (a Cloud), wherein image data and/or examination data must be stored geographically separated by an evaluation unit and therefore data transmission must take place. A typical problem definition of such an evaluation is comparing the x-ray dose absorbed by the patient for specific computed tomography imaging (of the head for example) with the national average. For this dose parameters for various device types must be calculated from data that is stored in different geographical locations by the evaluation unit. Furthermore the necessary data must also be accessible for the evaluation unit.